OpenMP* Advanced Issues
- When using functions instead ofpragmas,your code must be rewritten; rewrites can mean extra debugging, testing, and maintenance efforts.
- It becomes difficult to compile without OpenMP support.
- It is very easy to introduce simple bugs, as in the loop (below) that fails to print all the letters of the alphabet when the number of threads is not a multiple of 26.
- You lose the ability to adjust loop scheduling without creating your own work-queue algorithm, which is a lot of extra effort. You are limited by your own scheduling, which is mostly likely static scheduling as shown in the example.
- The underlying performance of the single-threaded code.
- CPU utilization, idle threads, and load balancing.
- The percentage of the application that is executed in parallel by multiple threads.
- The amount of synchronization and communication among the threads.
- The overhead needed to create, manage, destroy, and synchronize the threads, made worse by the number of single-to-parallel or parallel-to-single transitions called fork-join transitions.
- Performance limitations of shared resources such as memory, bus bandwidth, and CPU execution units.
- Memory conflicts caused by shared memory or falsely shared memory.